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Adaptive Sliding Mode Control for PMSG Wind Turbine Systems

Author

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  • Sung-Won Lee

    (Department of Electrical Engineering, Chungnam National University, Daejeon 34134, South Korea)

  • Kwan-Ho Chun

    (Department of Electrical Engineering, Chungnam National University, Daejeon 34134, South Korea)

Abstract

In this paper, variable speed PMSG wind turbine systems with unknown system parameters, such as vicious friction coefficient and total inertia, are considered. The errors and variations of wind speed are modeled as a disturbance in mechanical torque. In general, the optimum rotating speed is given based on the MPPT (Maximum Power Point Tracking) algorithm and the designed controller tracks the reference (optimum) rotating speed in spite of these parametric uncertainties and disturbances. In order to have a desired rotor speed, a sliding mode current controller is proposed to have robustly stabilizing torque input. From the robustly stabilizing q-axis current i q , q-axis voltage input u q is obtained. Additionally, the d-axis control input u d is designed to regulate the d-axis current i d . The adaptive estimator, for the total inertia J and the viscous friction coefficient F , is designed by a backstepping control technique. The robust stability of the closed-loop system is shown using a Lyapunov function. The proposed controller is verified via a simulation using MATLAB/Simulink.

Suggested Citation

  • Sung-Won Lee & Kwan-Ho Chun, 2019. "Adaptive Sliding Mode Control for PMSG Wind Turbine Systems," Energies, MDPI, vol. 12(4), pages 1-17, February.
  • Handle: RePEc:gam:jeners:v:12:y:2019:i:4:p:595-:d:205612
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    References listed on IDEAS

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    1. Oscar Barambones, 2012. "Sliding Mode Control Strategy for Wind Turbine Power Maximization," Energies, MDPI, vol. 5(7), pages 1-21, July.
    2. Abdullah, M.A. & Yatim, A.H.M. & Tan, C.W. & Saidur, R., 2012. "A review of maximum power point tracking algorithms for wind energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(5), pages 3220-3227.
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    Cited by:

    1. Kenneth E. Okedu, 2022. "Augmentation of DFIG and PMSG Wind Turbines Transient Performance Using Different Fault Current Limiters," Energies, MDPI, vol. 15(13), pages 1-25, June.
    2. Kenneth E. Okedu & S. M. Muyeen, 2022. "Comparative Performance of DFIG and PMSG Wind Turbines during Transient State in Weak and Strong Grid Conditions Considering Series Dynamic Braking Resistor," Energies, MDPI, vol. 15(23), pages 1-22, December.
    3. Zhicheng Lin & Song Zheng & Zhicheng Chen & Rong Zheng & Wang Zhang, 2019. "Application Research of the Parallel System Theory and the Data Engine Approach in Wind Energy Conversion System," Energies, MDPI, vol. 12(5), pages 1-20, March.
    4. Walter Gil-González & Oscar Danilo Montoya & Luis Fernando Grisales-Noreña & Alberto-Jesus Perea-Moreno & Quetzalcoatl Hernandez-Escobedo, 2020. "Optimal Placement and Sizing of Wind Generators in AC Grids Considering Reactive Power Capability and Wind Speed Curves," Sustainability, MDPI, vol. 12(7), pages 1-20, April.
    5. Youjie Ma & Long Tao & Xuesong Zhou & Wei Li & Xueqi Shi, 2019. "Analysis and Control of Wind Power Grid Integration Based on a Permanent Magnet Synchronous Generator Using a Fuzzy Logic System with Linear Extended State Observer," Energies, MDPI, vol. 12(15), pages 1-19, July.
    6. Youjie Ma & Faqing Zhao & Xuesong Zhou & Mao Liu & Bao Yang, 2019. "DC Side Bus Voltage Control of Wind Power Grid-Connected Inverter Based on Second-Order Linear Active Disturbance Rejection Control," Energies, MDPI, vol. 12(22), pages 1-20, November.
    7. Mojtaba Nasiri & Saleh Mobayen & Behdad Faridpak & Afef Fekih & Arthur Chang, 2020. "Small-Signal Modeling of PMSG-Based Wind Turbine for Low Voltage Ride-Through and Artificial Intelligent Studies," Energies, MDPI, vol. 13(24), pages 1-18, December.
    8. Youjie Ma & Xia Yang & Xuesong Zhou & Luyong Yang & Yongliang Zhou, 2020. "Dual Closed-Loop Linear Active Disturbance Rejection Control of Grid-Side Converter of Permanent Magnet Direct-Drive Wind Turbine," Energies, MDPI, vol. 13(5), pages 1-21, March.
    9. Zholtayev, Darkhan & Rubagotti, Matteo & Do, Ton Duc, 2022. "Adaptive super-twisting sliding mode control for maximum power point tracking of PMSG-based wind energy conversion systems," Renewable Energy, Elsevier, vol. 183(C), pages 877-889.
    10. Sameh Mahjoub & Larbi Chrifi-Alaoui & Saïd Drid & Nabil Derbel, 2023. "Control and Implementation of an Energy Management Strategy for a PV–Wind–Battery Microgrid Based on an Intelligent Prediction Algorithm of Energy Production," Energies, MDPI, vol. 16(4), pages 1-26, February.
    11. Pan, Lin & Wang, Xudong, 2020. "Variable pitch control on direct-driven PMSG for offshore wind turbine using Repetitive-TS fuzzy PID control," Renewable Energy, Elsevier, vol. 159(C), pages 221-237.
    12. Nicholas Hawkins & Michael L. McIntyre, 2021. "A Robust Nonlinear Controller for PMSG Wind Turbines," Energies, MDPI, vol. 14(4), pages 1-17, February.
    13. Shiref A. Abdalla & Shahrum S. Abdullah, 2019. "Performance Improvements of Induction Motor Drive Supplied by Hybrid Wind and Storage Generation System Based on Mine Blast Algorithm," Energies, MDPI, vol. 12(15), pages 1-17, July.

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